61 citations · 86 across the 4 of their papers we have counts for
6 papers
Multi-scale Deep Neural Network (MscaleDNN) Methods for Oscillatory Stokes Flows in Complex Domains
Bo Wang, Wenzhong Zhang, Wei Cai
In this paper, we study a multi-scale deep neural network (MscaleDNN) as a meshless numerical method for computing oscillatory Stokes flows in complex domains. The MscaleDNN employ…
Multi-scale Deep Neural Network (MscaleDNN) for Solving Poisson-Boltzmann Equation in Complex Domains
Ziqi Liu, Wei Cai, Zhi-Qin John Xu
In this paper, we propose multi-scale deep neural networks (MscaleDNNs) using the idea of radial scaling in frequency domain and activation functions with compact support. The radi…
A Note on StiffDNN -- a DNN for Stiff Dynamic Systems
Wei Cai
In this note, we will present a specially designed deep neural network (DNN), which will target components of the solution of different time rate individually through perspective o…
Multi-scale Deep Neural Networks for Solving High Dimensional PDEs
Wei Cai, Zhi-Qin John Xu
In this paper, we propose the idea of radial scaling in frequency domain and activation functions with compact support to produce a multi-scale DNN (MscaleDNN), which will have the…
A Phase Shift Deep Neural Network for High Frequency Approximation and Wave Problems
Wei Cai, Xiaoguang Li, Lizuo Liu
In this paper, we propose a phase shift deep neural network (PhaseDNN), which provides a uniform wideband convergence in approximating high frequency functions and solutions of wav…
PhaseDNN - A Parallel Phase Shift Deep Neural Network for Adaptive Wideband Learning
Wei Cai, Xiaoguang Li, Lizuo Liu
In this paper, we propose a phase shift deep neural network (PhaseDNN) which provides a wideband convergence in approximating a high dimensional function during its training of the…